Open Access
SPEA2: Improving the Strength Pareto Evolutionary Algorithm For Multiobjective Optimization
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The article was published on 2002-01-01 and is currently open access. It has received 1972 citations till now. The article focuses on the topics: Pareto principle & Multi-objective optimization.read more
Citations
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Journal ArticleDOI
Self-Organizing Map-Based Weight Design for Decomposition-Based Many-Objective Evolutionary Algorithm
Fangqing Gu,Yiu-ming Cheung +1 more
TL;DR: A novel weight design method based on SOM is proposed, which can be integrated with most of the decomposition-based algorithms for solving MaOPs and is compared with some state-of-the-art algorithms on eleven redundancy problems and eight nonredundancy problems, respectively.
Journal ArticleDOI
A Bayesian approach to constrained single- and multi-objective optimization
TL;DR: An extended domination rule is used to handle objectives and constraints in a unified way, and a corresponding expected hyper-volume improvement sampling criterion is proposed, which is compared to state-of-the-art algorithms for single- and multi-objective constrained optimization.
Dissertation
Analyse et évaluation de techniques de commutation Ethernet pour l'interconnexion des systèmes avioniques
TL;DR: In this article, the authors propose a methode de preuve du determinisme for reseau de avioniques, utilisant la theorie du Network Calculus, and propose egalement des optimisations of the reseau.
Journal ArticleDOI
Multiobjective Contaminant Sensor Network Design for Water Distribution Systems
Ami Preis,Avi Ostfeld +1 more
TL;DR: In this study a multiobjective model for water distribution system optimal sensor placement using the nondominated sorted genetic algorithm II is developed and demonstrated using two water distribution systems of increasing complexity.
Journal ArticleDOI
Multi-objective genetic fuzzy classifiers for imbalanced and cost-sensitive datasets
TL;DR: The FRBC selected from the convex hull produced by the three-objective optimization approach achieves the lowest classification cost among the techniques used as comparison in two specific medical applications.